Triple
T27556843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whittle likelihood |
E695659
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | time series analysis method |
C25327
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: time series analysis method Context triple: [Whittle likelihood, instanceOf, time series analysis method]
-
A.
U.S. economic time series
A U.S. economic time series is a chronologically ordered sequence of quantitative observations that track the evolution of a specific economic indicator (such as GDP, inflation, or unemployment) in the United States over time.
-
B.
statistical methodology
Statistical methodology is the collection of principles, techniques, and procedures used to design studies, collect data, and analyze and interpret quantitative information to draw valid and reliable conclusions.
-
C.
cyclical forecasting system
A cyclical forecasting system is a predictive framework that analyzes recurring patterns and periodic trends in data to anticipate future states or events over repeating time intervals.
-
D.
statistical inference method
chosen
A statistical inference method is a systematic procedure for drawing conclusions about a population’s properties based on observed sample data, often quantifying uncertainty through probabilities or confidence measures.
-
E.
technique in analysis
A technique in analysis is a systematic method or procedure used to examine, simplify, or solve mathematical problems involving limits, continuity, differentiation, integration, or related structures.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ef5387e97c8190a9dab040d21cd048 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 27, 2026, 1:37 p.m.